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moving_estimate_from_inventory

Estimate moving volume and weight from inventory text or item lists, parsing quantities and typos and flagging unmatched items for review.

Instructions

Estimate the volume (cu ft / m3) and weight of a move from a list of belongings.

Give inventory_text (one block or a list of lines) such as "queen bed, 3-seat sofa, 20 medium boxes", and/or structured items. Text understands quantities ("3x", "two", "a dozen"), plurals, small typos, "Bedroom:" headers and notes in parentheses. Items it cannot match are returned in unresolved and are NOT in the total; assumed sizes are listed in needs_review: ask the user about them rather than hiding them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsNo
unitsNoboth
detailNosummary
default_roomNoUnassigned
inventory_textNo
include_recommendationsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations available, the description carries the full burden and does real work: it discloses that unmatched items land in 'unresolved' and are excluded from the total, and that assumed sizes surface in 'needs_review' with an instruction to ask the user. That is exactly the kind of behavioral disclosure that prevents a silently wrong estimate. It does not describe determinism or stability of the estimate, and the unresolved/needs_review guarantees are the only failure modes covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Roughly four sentences, front-loaded with the outcome (volume and weight), then input format, then edge-case behavior. The parenthetical examples ('3x', 'two', 'a dozen', 'Bedroom:') are dense but each one illustrates a distinct parsing capability rather than padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema covers return values, so the unresolved/needs_review mention is bonus context rather than a required gap-fill, and a pure estimator needs no auth or rate-limit disclosure. The remaining gap is the four undescribed input parameters — for a six-parameter tool with 0% schema coverage, an agent cannot confidently set units, detail, or include_recommendations from this description alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% across six parameters, so the description must compensate, and it only covers two of them: inventory_text (accepted as one block or a list of lines, with quantity/plural/typo/'Bedroom:' header handling spelled out) and items (structured alternative). units, detail, default_room, and include_recommendations — two of which are enums with non-obvious behavioral consequences — receive no explanation at all.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource with concrete output metrics: 'Estimate the volume (cu ft / m3) and weight of a move from a list of belongings.' The 'from a list of belongings' framing implicitly separates it from moving_estimate_from_scan and moving_estimate_object, but no sibling is named outright, so an agent must infer the boundary rather than read it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description tells the agent what to supply ('Give inventory_text ... and/or structured items') and gives one operating instruction ('ask the user about them rather than hiding them'), which implies the right context. It never states when to prefer this tool over the sibling estimators or what input shape rules out the alternatives, so usage is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.